{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a147bdd4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Zen of Python, by Tim Peters\n",
      "\n",
      "Beautiful is better than ugly.\n",
      "Explicit is better than implicit.\n",
      "Simple is better than complex.\n",
      "Complex is better than complicated.\n",
      "Flat is better than nested.\n",
      "Sparse is better than dense.\n",
      "Readability counts.\n",
      "Special cases aren't special enough to break the rules.\n",
      "Although practicality beats purity.\n",
      "Errors should never pass silently.\n",
      "Unless explicitly silenced.\n",
      "In the face of ambiguity, refuse the temptation to guess.\n",
      "There should be one-- and preferably only one --obvious way to do it.\n",
      "Although that way may not be obvious at first unless you're Dutch.\n",
      "Now is better than never.\n",
      "Although never is often better than *right* now.\n",
      "If the implementation is hard to explain, it's a bad idea.\n",
      "If the implementation is easy to explain, it may be a good idea.\n",
      "Namespaces are one honking great idea -- let's do more of those!\n"
     ]
    }
   ],
   "source": [
    "import this\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1832d482",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DwIEDC71PTlhYGHa7nbS0NAICAm74ztIJCQl069aNPn36MHjw4HzvtWvXjpdffpm33nqL1157jTvvvLPQdb3zzju88847ea8vXbrExo0bGTp0aN60P/74gzp16lxzHY0bN2bbtm2kpqby5ZdfMmDAAH7++WeFIRGREnbwzEWGxsazNykdiwWGdmjA8x0b4uFu7uCUglAJ8vV0549xXU3bdlFFR0fTokULPvvsM7p06cLu3btZtmxZocs0bdqUY8eOXfP9u+6667pXXCUmJtKhQwduv/12Pv7446vet9vt/Prrr7i7u3Pw4MHr7sezzz7Lo48+mvf68ccfp3fv3vTq1StvWs2aNQtdh5eXFw0aNACgVatWbNq0iSlTpjBr1qzrbl9ERIrmqy0nGbl4F5esNqpV9GJy32jubFjN7LKAMhSE1q5dy4QJE9iyZQunTp3im2++oWfPnsDlR1mMHDmS5cuXc/jwYQIDA+nUqRPvvvtuob/oxowZw9ixY/NNa9y4MXv37i2VfbBYLEUanioL/vSnPzF58mQSEhLo1KkToaGhhc5/s0NjCQkJdOjQgVatWjF79uwCjyhNmDCBvXv38vPPP9O1a1dmz57NoEGDrrnOKlWq5DvPyNfXl+Dg4LxgcyPsdvtVJ5KLiMiNyczJZdSS3Xy55SQAt9evyuS+UQQHmDcU9r/KzG/tjIwMWrRowVNPPZXvL3qAzMxM4uPjefPNN2nRogUXLlzg+eefp0ePHmzevLnQ9TZt2pRVq1blvfbwKDO7bKqYmBhefvll/vGPf/DZZ59dd/6bGRpLSEigffv2hIWFMXHiRJKT/3OpZEhICABbt25l1KhRfPnll9xxxx188MEHPP/889xzzz3Uq1ev+DtYBCNGjKB79+7UqVOH9PR0YmNjWbNmDd9/b855XiIi5cn+0+kMmRvPgTMXcbPA8x0bMfTeBri7la3HFZWZVNC9e/drXnkUGBhIXFxcvmnTpk2jTZs2HD9+vNBzQDw8PPJ+2cp/BAYG0rt3b5YtW5Z35K20xMXFcfDgQQ4ePEjt2rXzvWcYBllZWTzxxBMMHDiQBx98EIA///nPLFu2jCeffJK1a9fi7l70ob+iOnPmDP379+fUqVMEBgYSGRnJ999/T+fOnUt8WyIirsIwDBZtPsmopbvIstoJ9vdmymPRtKtf1ezSClRmglBxpaamYrFYqFSpUqHzHThwgJo1a+Lj40O7du0YP358ocEpOzs739BIWloacHl47srT5q+wWq0YhoHdbsduN+/SvxuVkJBATEwMnp6eRar/yiX6V/a5qPr373/N+wHZ7Xa8vLzYuXNn3usrvvnmm3zzXc+PP/5Y5HkB/vGPf1yzpmtNNwwDq9VaKsHsv135rP3vZ05KlvrsGOqzY5SFPmdk5zL62z0s2X4KgDsbVGVi72ZUrejt8LqKuj2LUdQb0DiQxWLJd47Q/8rKyuKOO+4gIiKCuXPnXnM9K1as4OLFizRu3JhTp04xduxYEhIS2LVrF/7+/gUuU9B5RQCxsbH4+fnlm3blaFNoaCheXl5F30GTpaSksG7dOgYMGMDGjRtp2LCh2SU5hZycHE6cOEFSUhK5ublmlyMiUqYkZMCc/e6cybLghsF9dex0rGlg1khYZmYmMTExpKamFnorFqcLQlarld69e3Py5EnWrFlTrPvMpKSkEBYWxgcffMDTTz9d4DwFHREKDQ3l7NmzV20rKyuLEydOEB4ejo9P2Tnx63rq1avHhQsXGDlyJC+99FKRlzMMg/T0dPz9/Qu91L68ysrK4ujRo4SGhpb699tqtRIXF0fnzp3x9PQs1W25MvXZMdRnxzCrz4ZhMH/zSd5evo+cXDvVA7yZ/GgkrcMqO6yGgqSlpVGtWrXrBiGnGhqzWq08+uijHDt2jB9//LHYN9urVKkSjRo1KvTSbG9vb7y9va+a7unpedUHy2azYbFYcHNzu+H76pjh6NGjN7TclSGjK/vsatzc3LBYLAV+FkqLI7flytRnx1CfHcORfU7PsjLi6118t+PyUNi9EcFM7NOCKhXMHyUpag+c5rfZlRB04MABVq1aRdWqxT/p6uLFixw6dIgaNWqUQoUiIiKuY1dCKg9+uI7vdpzCw83CiO4RfNK/dZkIQcVRZo4IXbx4Md+RmiNHjrBt2zaqVKlCjRo1eOSRR4iPj+e7777DZrORlJQEXL6XzJXzczp27MjDDz+cd2fhl19+mQcffJCwsDASExMZPXo07u7u9OvXr0RrL4Oji1IK9H0WEbn8s/Dzjcd4+7s95Njs1Krky4cx0bSsY+5Q2I0qM0Fo8+bNdOjQIe/18OHDARgwYABjxozJe0hoVFRUvuV++umnvGdkHTp0iLNnz+a9d/LkSfr168e5c+cICgrizjvvZOPGjQQFBZVIzVcOu2VmZhbrWVvinHJycgBK/YoxEZGyKvWSlde+3MHK3ZcPRnS5pToTHmlBoJ/zDnmWmSDUvn37Qv/iLspf4/977sv8+fNvtqxCubu7U6lSJc6cOQOAn59fuT6J2G63k5OTQ1ZWlsudI2S320lOTsbPz0835RQRl7TtRApDY+M5eeESnu4WRnRvwqA7wp3+955+ot+kKzdrvBKGyjPDMLh06RK+vr5O/8G/EW5ubtSpU8cl911EXJdhGHy67gjvrdyL1WZQp4of02KiiaxdyezSSoSC0E2yWCzUqFGD4ODgcn+zMKvVytq1a7n77rtd8soPLy8vlzsSJiKuLSUzh5cX7WDVntMA3Nc8hHd7RxLgU35+BygIlRB3d/dyf+6Iu7s7ubm5+Pj4uGQQEhFxJVuOnWdY7FYSU7PwcnfjzQea8MRtYeXuqLiCkIiIiOSx2w0+/uUwE77fh81uEF7Vj2kxLWlWK9Ds0kqFgpCIiIgAcO5iNi8t2s6afckA9GhRk3d6Naeid/mNC+V3z0RERKTIfjt8jufmb+V0WjbeHm6M6dGUx24NLXdDYf9LQUhERMSF2e0GM9Yc5IO4/dgNqB9UgWkxLWlSo3iPsXJWCkIiIiIuKjk9m+ELt/HLgcs3I+7VshZvPdSMCuV4KOx/uc6eioiISJ71B8/y/IJtJKdn4+vpzriHmtKndajZZTmcgpCIiIgLsdkNpq4+wNQfD2AY0Kh6RabHtKRhdX+zSzOFgpCIiIiLOJOWxXPzt7Lx8HkA+rYOZUyPpvh6le/74BVGQUhERMQFrN2fzIsLtnEuIwc/L3feebg5PaNrmV2W6RSEREREyrFcm51Jq/YzY80hDAOa1Ahgekw09YIqml1amaAgJCIiUk6dSr3Ec/O2sunoBQAeb1uHNx+4BR9P1x0K+18KQiIiIuXQT3vPMHzhNi5kWqno7cG7vZvzQGRNs8sqcxSEREREyhGrzc7EuD3MWnsYgGa1ApjWryXh1SqYXFnZpCAkIiJSTpzPhphPN7HtRCoAA9qF8cb9TfD20FDYtSgIiYiIlAOr9pxhwnZ3Mm2p+Pt4MOGRSLo1q2F2WWWegpCIiIgTy8m18+6Kvfzz1yOAhchaAUx/vBWhVfzMLs0pKAiJiIg4qRPnMxkaG8/2k5eHwtrXsDP9T22o4OttcmXOQ0FIRETECa3YeYpXv9pBelYugb6evNerKdmHN+Pl4WZ2aU5FQUhERMSJZFltvLN8D59tOAZAq7DKTO0XTXAFD5YfNrk4J6QgJCIi4iSOns1gSGw8uxPTAHj2nvq81KURnu5uWK1Wk6tzTgpCIiIiTmDp9kTe+HonF7NzqVLBi/cfbUGHxsFml+X0FIRERETKsCyrjbHf/sG8348D0Ca8ClP7RRMS6GNyZeWDgpCIiEgZdfDMRYbGxrM3KR2LBYZ2aMDzHRvi4a4TokuKgpCIiEgZ9HX8SUYu3kVmjo1qFb2Y1DeKuxoGmV1WuaMgJCIiUoZk5uQyesluFm05CUC7elWZ8lgUwQEaCisNCkIiIiJlxP7T6QyZG8+BMxdxs8DzHRsx9N4GuLtZzC6t3FIQEhERMZlhGCzafJJRS3eRZbUT5O/N1MeiaVe/qtmllXsKQiIiIibKyM5l5OJdfLM1AYC7GlZjUt8oqlXUYzIcocycdr527VoefPBBatasicViYfHixfneNwyDUaNGUaNGDXx9fenUqRMHDhy47nqnT59OeHg4Pj4+tG3blt9//72U9kBERKR49pxK48Fp6/hmawJuFnila2P+NaiNQpADlZkglJGRQYsWLZg+fXqB7//9739n6tSpzJw5k99++40KFSrQtWtXsrKyrrnOBQsWMHz4cEaPHk18fDwtWrSga9eunDlzprR2Q0RE5LoMw2Dub8d4aPqvHE7OICTAh/l/bseQDg1w0/lADlVmhsa6d+9O9+7dC3zPMAwmT57MyJEjeeihhwD47LPPqF69OosXL+axxx4rcLkPPviAwYMHM2jQIABmzpzJsmXL+Oc//8nrr79eOjsiIiJSiPQsKyO+3sl3O04B0L5xEB88GkWVCl4mV+aaykwQKsyRI0dISkqiU6dOedMCAwNp27YtGzZsKDAI5eTksGXLFkaMGJE3zc3NjU6dOrFhw4Zrbis7O5vs7Oy812lpl5/nYrVaXf45Llf239X74AjqtWOoz46hPv/H7sQ0nl+wg2PnM/FwszC8cwOevj0cNzfLTfdHfc6vqH1wiiCUlJQEQPXq1fNNr169et57/+vs2bPYbLYCl9m7d+81tzV+/HjGjh171fQffvgBPz+/4pZeLsXFxZldgstQrx1DfXYMV+6zYcAvSRYWH3PDZlio7GUwoFEutdL2sHLlnhLdliv3+b9lZmYWaT6nCEKONGLECIYPH573Oi0tjdDQULp06UJAQICJlZnParUSFxdH586d8fT0NLucck29dgz12TFcvc9pl6y8sXg33x+9fH5qx4gg3n24GZX8SrYXrt7n/3VlROd6nCIIhYSEAHD69Glq1KiRN/306dNERUUVuEy1atVwd3fn9OnT+aafPn06b30F8fb2xtv76rP1PT099cH6N/XCcdRrx1CfHcMV+7z9RApD58Vz4vwlPN0tjOjehEF3hGOxlN4J0a7Y54IUtQdl5qqxwtStW5eQkBBWr16dNy0tLY3ffvuNdu3aFbiMl5cXrVq1yreM3W5n9erV11xGRESkJBiGwafrjvDIzPWcOH+J0Cq+fPns7Tx1Z91SDUFSfGXmiNDFixc5ePBg3usjR46wbds2qlSpQp06dXjhhRd4++23adiwIXXr1uXNN9+kZs2a9OzZM2+Zjh078vDDDzN06FAAhg8fzoABA2jdujVt2rRh8uTJZGRk5F1FJiIiUtJSMnN4edEOVu25PCLRvVkI7/aOJNBXR2nKojIThDZv3kyHDh3yXl85T2fAgAHMmTOHV199lYyMDP785z+TkpLCnXfeycqVK/Hx+c9D6A4dOsTZs2fzXvft25fk5GRGjRpFUlISUVFRrFy58qoTqEVERErClmMXeG7eVhJSLuHl7sbIB5rw5G1hOgpUhpWZINS+fXsMw7jm+xaLhXHjxjFu3LhrznP06NGrpg0dOjTvCJGIiEhpsNsN/vHLYSZ8v49cu0F4VT+mxbSkWa1As0uT6ygzQUhERMQZnc/I4aWF2/hpXzIAD7aoyTsPN8PfR0NhzkBBSERE5Ab9fuQ8z83bSlJaFt4ebox+sCn92oRqKMyJKAiJiIgUk91u8NHPh/ggbj82u0G9oApMj2lJkxqufb85Z6QgJCIiUgzJ6dkMX7iNXw5cvjinV3Qt3urZjAre+pXqjPRdExERKaL1h87y/PxtJKdn4+PpxriHmtGnVW0NhTkxBSEREZHrsNkNPvzxAFNXH8BuQMPgisx4vCUNq/ubXZrcJAUhERGRQpxJy+L5+dvYcPgcAI+2rs3YHs3w9XI3uTIpCQpCIiIi17B2fzIvLtjGuYwc/Lzc+dvDzXg4urbZZUkJUhASERH5H7k2O5NW7WfGmkMYBkSE+DMtpiUNgiuaXZqUMAUhERGR/3Iq9RLPz9vG70fPAxDTtg6jHrgFH08NhZVHCkIiIiL/9tPeMwxfuI0LmVYqenvwTq/m9GhR0+yypBQpCImIiMuz2uxM/H4fs9YeBqBpzQCmx7QkvFoFkyuT0qYgJCIiLi0h5RLDYuOJP54CwIB2YYy4r4mGwlyEgpCIiLisuD9O8/Ki7aResuLv48Hfe0fSvXkNs8sSB1IQEhERl5OTa+fdFXv5569HAGhRO5AP+7WkTlU/kysTR1MQEhERl3LifCZDY+PZfjIVgKfuqMvr3SPw8nAzuTIxg4KQiIi4jJW7TvHKlztIz8ol0NeTiX1a0PmW6maXJSZSEBIRkXIvy2pj/PI9/GvDMQCi61Tiw37R1K6soTBXpyAkIiLl2tGzGQyJjWd3YhoAz9xdj5e7NsbTXUNhoiAkIiLl2LfbExnx9U4uZudS2c+TDx6NokNEsNllSRmiICQiIuVOltXGuO/+IPa34wC0Ca/ClH5R1Aj0NbkyKWsUhEREpFw5lHyRIXPj2ZuUjsUCQ9o34IVODfHQUJgUQEFIRETKjcVbE3jjm51k5tioVtGLSX2juKthkNllSRmmICQiIk7vUo6N0Ut3sXDzSQDa1avKlMeiCA7wMbkyKesUhERExKntP53OkLnxHDhzEYsFnu/YkGH3NsTdzWJ2aeIEFIRERMQpGYbBoi0nGbVkF1lWO0H+3kx5LIrb61czuzRxIgpCIiLidDKycxm5eBffbE0A4K6G1fjg0SiC/L1NrkycjYKQiIg4lT2n0hgSG8/h5AzcLDC8cyP+2r4BbhoKkxugICQiIk7BMAzm/X6Csd/uJjvXTkiAD1P7RdOmbhWzSxMnpiAkIiJlXnqWlTe+2cW32xMBaN84iA8ejaJKBS+TKxNnpyAkIiJl2q6EVIbGxnP0XCYebhZe6dqYwXfV01CYlAinuc1meHg4Fovlqq8hQ4YUOP+cOXOumtfHR/eTEBFxFoZh8PmGo/SasZ6j5zKpVcmXBc+045l76isESYlxmiNCmzZtwmaz5b3etWsXnTt3pk+fPtdcJiAggH379uW9tlj0H0dExBmkZVl5/asdLN+ZBECnJtWZ2CeSSn4aCpOS5TRBKCgo/y3S3333XerXr88999xzzWUsFgshISGlXZqIiJSg7SdSGDovnhPnL+HpbuH17k146o5w/TErpcJpgtB/y8nJ4YsvvmD48OGF/se4ePEiYWFh2O12WrZsyTvvvEPTpk0LXXd2djbZ2dl5r9PS0gCwWq1YrdaS2QEndWX/Xb0PjqBeO4b67BhF7bNhGMzZcJwJP+zHajOoXcmHKX1bEFk7kNzcXEeU6tT0ec6vqH2wGIZhlHItJW7hwoXExMRw/PhxatasWeA8GzZs4MCBA0RGRpKamsrEiRNZu3Ytu3fvpnbt2tdc95gxYxg7duxV02NjY/Hz8yuxfRARkf/IsMK8Q27svHD51NXIKnb61bfj55R/rktZkJmZSUxMDKmpqQQEBFxzPqcMQl27dsXLy4tvv/22yMtYrVaaNGlCv379eOutt645X0FHhEJDQzl79myhjXQFVquVuLg4OnfujKenp9nllGvqtWOoz45xvT5vPZ7CCwt3kJiahae7hRHdGvNE21ANhRWTPs/5paWlUa1atesGIafL2seOHWPVqlV8/fXXxVrO09OT6OhoDh48WOh83t7eeHtffYt2T09PfbD+Tb1wHPXaMdRnx/jfPtvtBv/45TATvt9Hrt0grKof02Na0qxWoIlVOj99ni8rag+cLgjNnj2b4OBg7r///mItZ7PZ2LlzJ/fdd18pVSYiIkV1PiOHlxZu46d9yQA8EFmD8b2a4++jX+DiWE4VhOx2O7Nnz2bAgAF4eOQvvX///tSqVYvx48cDMG7cOG677TYaNGhASkoKEyZM4NixY/zpT38yo3QREfm3TUfPMyx2K0lpWXh5uDH6wVuIaVNHQ2FiCqcKQqtWreL48eM89dRTV713/Phx3Nz+c3/ICxcuMHjwYJKSkqhcuTKtWrVi/fr13HLLLY4sWURE/s1uN5j+00E+iNuPzW5Qr1oFpj/ekiY1XPv8SzGXUwWhLl26cK1zu9esWZPv9aRJk5g0aZIDqhIRketJt8LTn8ez7uA5AB6OrsXbPZtRwdupfg1JOaRPoIiIlKrfjpzn79vdSbOew8fTjXEPNaNPq9oaCpMyQUFIRERKhc1uMO3Hg0xZvR+7YaFBUAVmPNGKRtX9zS5NJI+CkIiIlLgz6Vm8MH8b6w9dHgprG2Tn42fbEljB1+TKRPJTEBIRkRK17sBZXliwlbMXc/Dzcmfsg03wStyGn5d+5UjZo0+liIiUiFybncmrDjB9zUEMAyJC/JkW05Kwyt4sT9xmdnkiBVIQEhGRm5aUmsVz87fy+5HzAMS0rcOoB27Bx9NdDwGVMk1BSEREbsqafWcYvnA75zNyqOjtwTu9mtOjRcEPxBYpaxSERETkhlhtdt7/YT8zfz4EQNOaAUyLaUndahVMrkyk6BSERESk2BJTLjFs3la2HLsAQP92YbxxXxN8PN1NrkykeBSERESkWFb9cZqXv9xOSqYVfx8P/t47ku7Na5hdlsgNURASEZEiycm18/eVe/lk3REAWtQO5MN+LalT1c/kykRunIKQiIhc14nzmQydt5XtJ1IAeOqOurzePQIvD7fCFxQp4xSERESkUCt3JfHKl9tJz8ol0NeTiX1a0PmW6maXJVIiFIRERKRA2bk2xi/fy5z1RwGIrlOJD/tFU7uyhsKk/FAQEhGRqxw7l8HQ2K3sTEgF4Jl76vFyl8Z4umsoTMoXBSEREcnnux2JjPhqJ+nZuVT28+SDR6PoEBFsdlkipUJBSEREAMiy2njruz+Y+9txAG4Nr8zUftHUCNQT46X8UhASEREOJV9kyNx49ialY7HAX+6pz/DOjfDQUJiUcwpCIiIubvHWBN74ZieZOTaqVvBiUt8o7m4UZHZZIg6hICQi4qIu5dgYs3Q3CzafAOC2elWY8lg01QN8TK5MxHEUhEREXNCB0+kMiY1n/+mLWCzw3L0Nea5jQ9zdLGaXJuJQCkIiIi5m0eYTjFqym0tWG0H+3kzpG8XtDaqZXZaIKRSERERcREZ2LqOW7Oar+JMA3NmgGpP6RhHk721yZSLmURASEXEBe5PSGDI3nkPJGbhZYHjnRvylfQMNhYnLUxASESnHDMNg/qYTjFm6m+xcO9UDvJn6WDRt61U1uzSRMkFBSESknLqYncsbX+9k6fZEANo3DuL9Pi2oWlFDYSJXKAiJiJRDuxJSGRobz9Fzmbi7WXila2P+fFc93DQUJpKPgpCISDliGAZfbDzGW8v2kJNrp2agDx/GRNMqrIrZpYmUSQpCIiLlRFqWlde/2sHynUkAdGoSzIRHWlC5gpfJlYmUXQpCIiLlwI6TKQyN3crx85l4uFl4vXsET99ZF4tFQ2EihVEQEhFxYoZhMGf9Ud5ZvgerzaBWJV+mxUQTXaey2aWJOAWneazwmDFjsFgs+b4iIiIKXWbRokVERETg4+ND8+bNWb58uYOqFREpfamZVp75fAtjv/0Dq82ga9PqLH/uLoUgkWJwqiNCTZs2ZdWqVXmvPTyuXf769evp168f48eP54EHHiA2NpaePXsSHx9Ps2bNHFGuiEipiT9+gWGxW0lIuYSXuxv/d38T+rcL01CYSDE5VRDy8PAgJCSkSPNOmTKFbt268corrwDw1ltvERcXx7Rp05g5c2ZplikiUmrsdoNP1h3m7yv3kWs3CKvqx7R+LWleO9Ds0kScklMFoQMHDlCzZk18fHxo164d48ePp06dOgXOu2HDBoYPH55vWteuXVm8eHGh28jOziY7OzvvdVpaGgBWqxWr1XpzO+Dkruy/q/fBEdRrx3C2Pl/IzOHVr3axZv9ZAO5vFsJbD92Cv49Hmd4HZ+uzs1Kf8ytqHyyGYRilXEuJWLFiBRcvXqRx48acOnWKsWPHkpCQwK5du/D3979qfi8vL/71r3/Rr1+/vGkzZsxg7NixnD59+prbGTNmDGPHjr1qemxsLH5+fiWzMyIixXQoDT474E5KjgUPi0GvunZuDzbQSJhIwTIzM4mJiSE1NZWAgIBrzuc0R4S6d++e9+/IyEjatm1LWFgYCxcu5Omnny6x7YwYMSLfkaS0tDRCQ0Pp0qVLoY10BVarlbi4ODp37oynp6fZ5ZRr6rVjOEOf7XaDj385wvTfDmGzG9St6seUvi1oUuPqPwDLKmfoc3mgPud3ZUTnepwmCP2vSpUq0ahRIw4ePFjg+yEhIVcd+Tl9+vR1zzHy9vbG2/vq5/B4enrqg/Vv6oXjqNeOUVb7fPZiNsMXbmft/mQAekbV5O2Hm1PR2zl/dJfVPpc36vNlRe2B01w+/78uXrzIoUOHqFGjRoHvt2vXjtWrV+ebFhcXR7t27RxRnojITdl4+Bz3TfmFtfuT8fF04++9I5nUN8ppQ5BIWeU0/6NefvllHnzwQcLCwkhMTGT06NG4u7vnnQPUv39/atWqxfjx4wF4/vnnueeee3j//fe5//77mT9/Pps3b+bjjz82czdERAplsxtM/+kgk1ftx25Ag+CKTI9pSeMQ5xkKE3EmThOETp48Sb9+/Th37hxBQUHceeedbNy4kaCgIACOHz+Om9t/DnDdfvvtxMbGMnLkSN544w0aNmzI4sWLdQ8hESmzzqRn8eKCbfx68BwAj7SqzbiHmuLn5TQ/qkWcjtP875o/f36h769Zs+aqaX369KFPnz6lVJGISMlZd+AsLyzYxtmL2fh6uvN2z2b0blXb7LJEyj2nCUIiIuVRrs3OlNUHmPbTQQwDGlf3Z/rjLWkQXNHs0kRcgoKQiIhJklKzeG7+Vn4/ch6Afm1CGf1gU3w83U2uTMR1KAiJiJhgzb4zDF+4nfMZOVTwcuedXs15KKqW2WWJuBwFIRERB7La7Lz/w35m/nwIgFtqBDAtJpp6QRoKEzGDgpCIiIMkplxi2LytbDl2AYAnbwvj/+5voqEwERMpCImIOMCqP07z8pfbScm04u/twbu9I7k/suAbwoqI4ygIiYiUopxcOxO+38s/fjkCQPNagUyLiSasagWTKxMRUBASESk1J85nMnTeVrafSAFg0B3hvN49Am8PDYWJlBUKQiIipWDlriRe/XI7aVm5BPh4MKFPC7o2LfyhzyLieCUShFJSUqhUqVJJrEpExKll59oYv3wvc9YfBSAqtBIf9osmtIqfuYWJSIGK/fT59957jwULFuS9fvTRR6latSq1atVi+/btJVqciIgzOXYug0c+2pAXgv58dz0WPtNOIUikDCt2EJo5cyahoaEAxMXFERcXx4oVK+jevTuvvPJKiRcoIuIMlu04xQNT17EzIZXKfp78c2Br3rivCV4exf4xKyIOVOyhsaSkpLwg9N133/Hoo4/SpUsXwsPDadu2bYkXKCJSlmVZbby97A++2HgcgNZhlfkwJpoagb4mVyYiRVHsP1UqV67MiRMnAFi5ciWdOnUCwDAMbDZbyVYnIlKGHU6+yMMz1ueFoL+2r8/8P9+mECTiRIp9RKhXr17ExMTQsGFDzp07R/fu3QHYunUrDRo0KPECRUTKoiXbEnjj651k5NioWsGLD/pGcU+jILPLEpFiKnYQmjRpEuHh4Zw4cYK///3vVKx4+fk4p06d4q9//WuJFygiUpZcyrEx9tvdzN90+cj4bfWqMOWxaKoH+JhcmYjciGIHIU9PT15++eWrpr/44oslUpCISFl18Ew6Q+ZuZd/pdCwWGHZvQ57v2BB3N4vZpYnIDSpSEFq6dCndu3fH09OTpUuXFjpvjx49SqQwEZGy5MstJ3lz8S4uWW1Uq+jN1MeiuL1BNbPLEpGbVKQg1LNnT5KSkggODqZnz57XnM9iseiEaREpVzJzcnlz8W6+ij8JwB0NqjKpbxTB/hoKEykPihSE7HZ7gf8WESnP9iWl89e5WziUnIGbBV7o1IghHRpoKEykHCnRZ41lZmbi56c7qIqIczMMgwWbTjB66W6yc+1UD/BmymPR3FavqtmliUgJK/Z9hDp27EhCQsJV03/77TeioqJKoiYREdNczM7lhQXbeP3rnWTn2rm7URDLn7tLIUiknCp2EPLx8SEyMjLveWN2u50xY8Zw1113cd9995V4gSIijrI7MZUeH65jybZE3N0svNqtMXMG3krVit5mlyYipaTYQ2PLli1j+vTpPPXUUyxZsoSjR49y7NgxvvvuO7p06VIaNYqIlCrDMPh84zHe+u4PcnLt1Aj04cN+0bQOr2J2aSJSym7oHKEhQ4Zw8uRJ3nvvPTw8PFizZg233357SdcmIlLqLuXCCwt3sHzXaQA6RgQzsU8LKlfwMrkyEXGEYg+NXbhwgd69e/PRRx8xa9asvIeuzpgxozTqExEpNbsS0piww53lu07j4WZh5P1N+GRAa4UgERdS7CNCzZo1o27dumzdupW6desyePBgFixYwF//+leWLVvGsmXLSqNOEZESYxgG/1p/lL8t34PVZqFWJR+mxbQkuk5ls0sTEQcr9hGhZ599lrVr11K3bt28aX379mX79u3k5OSUaHEiIiUtNdPKs19sYcy3f2C1GURWsbPkr+0UgkRcVLGPCL355psFTq9duzZxcXE3XZCISGnZevwCw+Zt5eSFS3i5u/F6t0ZUObeLQF9Ps0sTEZPc8A0VMzMzOX78+FVHgSIjI2+6KBGRkmQYBp/8coT3Vu4l125Qp4of02NaElHdj+XLd5ldnoiYqNhBKDk5mUGDBrFixYoC39ezxkSkLLmQkcPLi7azeu8ZAO6PrMH4Xs0J8PHEarWaXJ2ImK3Y5wi98MILpKSk8Ntvv+Hr68vKlSv517/+RcOGDa/7ZPqbMX78eG699Vb8/f3zHv66b9++QpeZM2cOFosl35ePjx6UKOIqNh89z31Tf2H13jN4ebjxds9mTOsXTYCPhsJE5LJiHxH68ccfWbJkCa1bt8bNzY2wsDA6d+5MQEAA48eP5/777y+NOvn5558ZMmQIt956K7m5ubzxxht06dKFP/74gwoVKlxzuYCAgHyByWLRwxJFyju73WDm2kO8/8N+bHaDutUqMC0mmqY1A80uTUTKmGIHoYyMDIKDgwGoXLkyycnJNGrUiObNmxMfH1/iBV6xcuXKfK/nzJlDcHAwW7Zs4e67777mchaLhZCQkFKrS0TKlrMXsxm+cDtr9ycD0DOqJm8/3JyK3iX6jGkRKSeK/ZOhcePG7Nu3j/DwcFq0aMGsWbMIDw9n5syZ1KhRozRqLFBqaioAVaoUfgv8ixcvEhYWht1up2XLlrzzzjs0bdr0mvNnZ2eTnZ2d9zotLQ0Aq9Xq8ucTXNl/V++DI6jXN+a3I+cZvmgnZ9Kz8fZwY/QDETzSshYWi1FgL9Vnx1CfHUN9zq+ofbAYhmEUZ8VffPEFubm5DBw4kC1bttCtWzfOnz+Pl5cXc+bMoW/fvjdUcHHY7XZ69OhBSkoK69atu+Z8GzZs4MCBA0RGRpKamsrEiRNZu3Ytu3fvpnbt2gUuM2bMGMaOHXvV9NjYWPz8/EpsH0Sk5NgNiEuwsOKEGwYWqvsaDGxko6b+y4q4rMzMTGJiYkhNTSUgIOCa8xU7CBW0ob1791KnTh2qVat2M6sqsr/85S+sWLGCdevWXTPQFMRqtdKkSRP69evHW2+9VeA8BR0RCg0N5ezZs4U20hVYrVbi4uLo3Lkznp462bQ0qddFl5yezctf7mT94fMAPBxdkzEPRODndf0D3uqzY6jPjqE+55eWlka1atWuG4RuatD8119/pXXr1rRs2fJmVlMsQ4cO5bvvvmPt2rXFCkEAnp6eREdHc/DgwWvO4+3tjbe3d4HL6oN1mXrhOOp14X49eJbn52/j7MVsfD3deatnMx5pVbyfC6A+O4r67Bjq82VF7UGxL5//b927dychIeFmVlFkhmEwdOhQvvnmG3788cd8j/goKpvNxs6dOx16LpOIlDyb3eCDH/bxxKe/cfZiNo2qV2Tp0DtuKASJiGu7qSNCNzmqVixDhgwhNjaWJUuW4O/vT1JSEgCBgYH4+voC0L9/f2rVqsX48eMBGDduHLfddhsNGjQgJSWFCRMmcOzYMf70pz85rG4RKVmn07J4bt5WfjtyeSjssVtDGf1gU3y93E2uTESckdNcT/rRRx8B0L59+3zTZ8+ezcCBAwE4fvw4bm7/Och14cIFBg8eTFJSEpUrV6ZVq1asX7+eW265xVFli0gJ+nl/Mi8u2Mb5jBwqeLnzTq/mPBRVy+yyRMSJFTsIDRgwgKeffpq7776bWbNmUb169dKo6ypFOfq0Zs2afK8nTZrEpEmTSqkiEXGUXJudD+L2M2PNIQCa1Ahgekw09YIqmlyZiDi7Yp8jlJqaSqdOnWjYsCFHjhwhJSWlFMoSEbksMeUSj328MS8EPXFbHb756+0KQSJSIoodhBYvXkxCQgJ/+ctfWLhwIeHh4XTv3p0vv/xSN3ESkRL1497T3Df1FzYfu0BFbw+mxUTzds/m+HjqfCARKRk3dNVYUFAQw4cPZ/v27fz22280aNCAJ598kpo1a/Liiy9y4MCBkq5TRFyI1WbnneV7eGrOZlIyrTSvFciy5+7kgciaZpcmIuXMTV0+f+rUKeLi4oiLi8Pd3Z377ruPnTt3csstt+jcHBG5IScvZNJn5gY+XnsYgIG3h/PlX9oRVvXaD1cWEblRxT5Z2mq1snTpUmbPns0PP/xAZGQkL7zwAjExMXl3bvzmm2946qmnePHFF0u8YBEpv77fncQri7aTlpVLgI8Hf3+kBd2a6aHJIlJ6ih2EatSogd1up1+/fvz+++9ERUVdNU+HDh2oVKlSCZQnIq4gJ9fO+BV7mP3rUQBahFZiWr9oQqvoYWEiUrqKHYQmTZpEnz598PHxueY8lSpV4siRIzdVmIi4huPnMhk6L54dJ1MBGHxXXV7pGoGXx02N3IuIFEmxg9CTTz5ZGnWIiAtavvMUr325g/TsXCr5efJ+nxZ0bOKYe5OJiIAT3VlaRMqPLKuNvy3bw+cbjwHQOqwyU/tFU7OSr8mViYirURASEYc6cjaDIXPj+eNUGgB/bV+fFzs3wtNdQ2Ei4ngKQiLiMEu2JfDG1zvJyLFRpYIXHzzagvaNg80uS0RcmIKQiJS6LKuNMUt3M3/TCQDa1K3C1MeiCQm89kUXIiKOoCAkIqXq4Jl0hszdyr7T6VgsMKxDA57r2BAPDYWJSBmgICQipebLLSd5c/EuLlltVKvozeS+UdzZsJrZZYmI5FEQEpESl5mTy5uLd/NV/EkA7mhQlUl9owj211CYiJQtCkIiUqL2JaUzJDaeg2cu4maBFzo1YkiHBri7WcwuTUTkKgpCIlIiDMNg4eYTjFqym+xcO8H+3kztF81t9aqaXZqIyDUpCInITbuYncvIb3ayeFsiAHc1rMakvlFUq+htcmUiIoVTEBKRm/JHYhpDY+M5fDYDdzcLL3VpxLN318dNQ2Ei4gQUhETkhhiGwdzfjjPuuz/IybVTI9CHqf2iuTW8itmliYgUmYKQiBRbWpaVEV/vZNmOUwDcGxHMxD4tqFLBy+TKRESKR0FIRIpl58lUhs6L59i5TDzcLLzarTF/urOehsJExCkpCIlIkRiGwb/WH+Wd5XvJsdmpVcmXD2OiaVmnstmliYjcMAUhEbmu1Ewrr361ne93nwag8y3VmfhICwL9PE2uTETk5igIiUihtp1IYWhsPCcvXMLT3cKI7k0YdEc4FouGwkTE+SkIiUiBDMPg03VHeHfFXnLtBqFVfJnWryUtQiuZXZqISIlREBKRq6Rk5vDyou2s2nMGgPuah/Bu70gCfDQUJiLli4KQiOSz5dh5hsVuJTE1Cy93N958oAlP3BamoTARKZcUhEQEALvdYNbaw0z8YR82u0F4VT+mxbSkWa1As0sTESk1CkIiwrmL2by0aDtr9iUD0KNFTd7p1ZyK3voRISLlm37Kibi43w6f47n5Wzmdlo23hxtjezSl762hGgoTEZfgZnYBxTV9+nTCw8Px8fGhbdu2/P7774XOv2jRIiIiIvDx8aF58+YsX77cQZWKlG02u8GHqw/Q7x8bOZ2WTf2gCiwZegePtamjECQiLsOpgtCCBQsYPnw4o0ePJj4+nhYtWtC1a1fOnDlT4Pzr16+nX79+PP3002zdupWePXvSs2dPdu3a5eDKRcqW5PRsBvzzd96P24/dgN4ta/PtsDuJCAkwuzQREYdyqiD0wQcfMHjwYAYNGsQtt9zCzJkz8fPz45///GeB80+ZMoVu3brxyiuv0KRJE9566y1atmzJtGnTHFy5SNmx/uBZ7pv6C+sOnsXX052JfVrw/qMt8PPSSLmIuB6n+cmXk5PDli1bGDFiRN40Nzc3OnXqxIYNGwpcZsOGDQwfPjzftK5du7J48eJrbic7O5vs7Oy812lpaQBYrVasVutN7IHzu7L/rt4HRyiNXtvsBtN+OsT0nw9jGNAwuAJT+ragYXBFl/2e6jPtGOqzY6jP+RW1D04ThM6ePYvNZqN69er5plevXp29e/cWuExSUlKB8yclJV1zO+PHj2fs2LFXTf/hhx/w8/O7gcrLn7i4OLNLcBkl1evUHPjsgBsH0y4fBG4XbKdXeCoHNq/lQIlswbnpM+0Y6rNjqM+XZWZmFmk+pwlCjjJixIh8R5HS0tIIDQ2lS5cuBAS49vkTVquVuLg4OnfujKen7jBcmkqy178cPMvYL3dyPsNKBS93xvW4hR4tapRQpc5Nn2nHUJ8dQ33O78qIzvU4TRCqVq0a7u7unD59Ot/006dPExISUuAyISEhxZofwNvbG29v76ume3p66oP1b+qF49xMr3Ntdj6I28+MNYcAaFIjgOkx0dQLqliSJZYL+kw7hvrsGOrzZUXtgdOcLO3l5UWrVq1YvXp13jS73c7q1atp165dgcu0a9cu3/xw+ZDhteYXKS9OpV6i3z825oWgx9vW4Zu/3q4QJCLyP5zmiBDA8OHDGTBgAK1bt6ZNmzZMnjyZjIwMBg0aBED//v2pVasW48ePB+D555/nnnvu4f333+f+++9n/vz5bN68mY8//tjM3RApVT/uPc1LC7dzIdNKRW8P3u3dnAcia5pdlohImeRUQahv374kJyczatQokpKSiIqKYuXKlXknRB8/fhw3t/8c5Lr99tuJjY1l5MiRvPHGGzRs2JDFixfTrFkzs3ZBpNRYbXYmfL+Pj9ceBqBZrQCmx7QkrGoFkysTESm7nCoIAQwdOpShQ4cW+N6aNWuumtanTx/69OlTylWJmOvkhUyGzdvK1uMpAAy8PZwR90Xg7eFubmEiImWc0wUhEcnvh91JvLxoO2lZufj7eDDhkUi6NdNVYSIiRaEgJOKkcnLtjF+xh9m/HgWgRWglpvWLJrSK7nclIlJUCkIiTuj4uUyGzotnx8lUAP50Z11e7RaBl4fTXAgqIlImKAiJOJnlO0/x2pc7SM/OJdDXk/f7tKDTLdWvv6CIiFxFQUjESWRZbfxt2R4+33gMgFZhlZnaL5palXxNrkxExHkpCIk4gSNnMxgaG8/uxMu3jH/2nvq81KURnu4aChMRuRkKQiJl3NLtiYz4agcZOTaqVPDi/Udb0KFxsNlliYiUCwpCImVUjg1GLvmDBZtPAtAmvApT+0UTEuhjcmUiIuWHgpBIGXQoOYMPdrlzKvMkFgsM7dCA5zs2xENDYSIiJUpBSKSM+Tr+JCMX7yIzx0LVCl5MeSyaOxtWM7ssEZFySUFIpIzIzMll9JLdLNpyeSisYYCdfz3bjppV9MR4EZHSoiAkUgbsP53OkLnxHDhzETcLDO1Qn7qZ+wjy9za7NBGRck0nHIiYyDAMFm46QY9p6zhw5iLB/t7M/dNtDOtQHzeL2dWJiJR/OiIkYpKM7FxGLt7FN1sTALirYTUm9Y2iWkVvrFarydWJiLgGBSERE+w5lcaQufEcPpuBu5uF4Z0b8Zd76uOmw0AiIg6lICTiQIZhEPv7ccZ++wc5uXZCAnz4MCaaW8OrmF2aiIhLUhAScZD0LCsjvt7JdztOAdChcRDvPxpFlQpeJlcmIuK6FIREHGBXQipDYuM5di4TDzcLr3ZrzJ/urKehMBERkykIiZQiwzD4bMMx/rZsDzk2O7Uq+fJhTDQt61Q2uzQREUFBSKTUpF6y8tqXO1i5OwmAzrdUZ8IjkVTy01CYiEhZoSAkUgq2nUhhaGw8Jy9cwtPdwuvdm/DUHeFYLBoKExEpSxSEREqQYRh8uu4I767YS67dILSKL9P6taRFaCWzSxMRkQIoCImUkJTMHF5etJ1Ve84A0L1ZCO/2jiTQ19PkykRE5FoUhERKwJZj5xkWu5XE1Cy83N0Y+UATnrwtTENhIiJlnIKQyE2w2w0+/uUwE77fh81uEF7Vj2kxLWlWK9Ds0kREpAgUhERu0LmL2by0aDtr9iUD8GCLmrzzcDP8fTQUJiLiLBSERG7Ab4fP8dz8rZxOy8bbw40xPZry2K2hGgoTEXEyCkIixWC3G8xYc5AP4vZjN6BeUAWmx7SkSY0As0sTEZEboCAkUkTJ6dkMX7iNXw6cBaBXdC3e6tmMCt76byQi4qz0E1ykCNYfPMvzC7aRnJ6Nj6cb4x5qRp9WtTUUJiLi5BSERAphsxtMXX2AqT8ewDCgUfWKTItpSaPq/maXJiIiJcDN7AKK4ujRozz99NPUrVsXX19f6tevz+jRo8nJySl0ufbt22OxWPJ9Pfvssw6qWpzdmbQsHv9kI1NWXw5Bj7auzZIhdyoEiYiUI05xRGjv3r3Y7XZmzZpFgwYN2LVrF4MHDyYjI4OJEycWuuzgwYMZN25c3ms/P7/SLlfKgbX7k3lxwTbOZeTg5+XO3x5uxsPRtc0uS0RESphTBKFu3brRrVu3vNf16tVj3759fPTRR9cNQn5+foSEhJR2iVJO5NrsTFq1nxlrDmEYEBHiz/THW1I/qKLZpYmISClwiiBUkNTUVKpUqXLd+ebOncsXX3xBSEgIDz74IG+++WahR4Wys7PJzs7Oe52WlgaA1WrFarXefOFO7Mr+l9c+nErNYviiHWw+lgJAv1tr80b3xvh4ujt8n8t7r8sK9dkx1GfHUJ/zK2ofLIZhGKVcS4k7ePAgrVq1YuLEiQwePPia83388ceEhYVRs2ZNduzYwWuvvUabNm34+uuvr7nMmDFjGDt27FXTY2NjNaxWjv1xwcIXB93IyLXg7W7Qr56d6GpO919DRET+LTMzk5iYGFJTUwkIuPa93kwNQq+//jrvvfdeofPs2bOHiIiIvNcJCQncc889tG/fnk8++aRY2/vxxx/p2LEjBw8epH79+gXOU9ARodDQUM6ePVtoI12B1WolLi6Ozp074+lZPh4jYbXZ+WDVQT5ZdxSApjX9mfJoC8Kqmht6y2OvyyL12THUZ8dQn/NLS0ujWrVq1w1Cpg6NvfTSSwwcOLDQeerVq5f378TERDp06MDtt9/Oxx9/XOzttW3bFqDQIOTt7Y23t/dV0z09PfXB+rfy0ouTFzIZNm8rW4+nADDw9nBG3BeBt4e7uYX9l/LS67JOfXYM9dkx1OfLitoDU4NQUFAQQUFBRZo3ISGBDh060KpVK2bPno2bW/Gv/N+2bRsANWrUKPayUr78sDuJV77cQeolK/4+Hkx4JJJuzfS5EBFxNU5xH6GEhATat29PnTp1mDhxIsnJySQlJZGUlJRvnoiICH7//XcADh06xFtvvcWWLVs4evQoS5cupX///tx9991ERkaatStispxcO2O/3c2fP99C6iUrLWoHsvy5uxSCRERclFNcNRYXF8fBgwc5ePAgtWvnv5fLlVOcrFYr+/btIzMzEwAvLy9WrVrF5MmTycjIIDQ0lN69ezNy5EiH1y9lw/FzmQydF8+Ok6kAPH1nXV7rFoGXh1P8PSAiIqXAKYLQwIEDr3suUXh4OP993ndoaCg///xzKVcmzmLFzlO8+uUO0rNzCfT15P0+Leh0S3WzyxIREZM5RRASuVFZVhvvLN/DZxuOAdCyTiU+jGlJrUq+JlcmIiJlgYKQlFtHzmYwNDae3YmXb4r5zD31eLlLYzzdNRQmIiKXKQhJubR0eyJvfL2Ti9m5VKngxfuPtqBD42CzyxIRkTJGQUjKlSyrjbHf/sG8348D0Ca8ClP7RRMS6GNyZSIiUhYpCEm5cfDMRYbGxrM3KR2LBYZ2aMDzHRvioaEwERG5BgUhKRe+jj/JyMW7yMyxUa2iF5P6RnFXw6LdrFNERFyXgpA4tUs5NkYt2cWiLScBaFevKlMeiyI4QENhIiJyfQpC4rT2n05nyNx4Dpy5iMUCz3dsyLB7G+LuZjG7NBERcRIKQuJ0DMNg0ZaTjFqyiyyrnSB/b6Y8FsXt9auZXZqIiDgZBSFxKhnZuYxcvItvtiYAcFfDakzqG0W1it4mVyYiIs5IQUicxp5TaQyJjedwcgZuFnipS2P+ck993DQUJiIiN0hBSMo8wzCY9/sJxny7m5xcOyEBPkztF02bulXMLk1ERJycgpCUaelZVt74Zhffbk8EoEPjIN5/NIoqFbxMrkxERMoDBSEps3YlpDI0Np6j5zLxcLPwarfG/OnOehoKExGREqMgJGWOYRh8vvEYb3+3hxybnVqVfJnaL5pWYZXNLk1ERMoZBSEpU1IvWXn9qx2s2JUEQKcm1ZnYJ5JKfhoKExGRkqcgJGXG9hMpDJ0Xz4nzl/B0tzCiexMG3RGOxaKhMBERKR0KQmI6wzD4569HeXfFHqw2g9Aqvkzr15IWoZXMLk1ERMo5BSExVUpmDi8v2sGqPacB6N4shHd7RxLo62lyZSIi4goUhMQ0W45d4Ll5W0lIuYSXuxsjH2jCk7eFaShMREQcRkFIHM5uN/j4l8NM+H4fNrtBeFU/psW0pFmtQLNLExERF6MgJA517mI2Ly3azpp9yQA82KIm7zzcDH8fDYWJiIjjKQiJw/x+5DzD5sVzOi0bbw83Rj/YlH5tQjUUJiIiplEQklJntxvMWHOQD+L2YzegXlAFpse0pEmNALNLExERF6cgJKUqOT2b4Qu38cuBswD0iq7FWz2bUcFbHz0RETGffhtJqVl/8CzPL9hGcno2Pp5ujHuoGX1a1dZQmIiIlBkKQlLibHaDqasPMPXHAxgGNAyuyPTHW9Kour/ZpYmIiOSjICQl6kxaFs/P38aGw+cAeLR1bcb2aIavl7vJlYmIiFxNQUhKzC8HknlxwTbOXszBz8udt3s2o1fL2maXJSIick0KQnLTcm12Jq86wPQ1BzEMiAjxZ1pMSxoEVzS7NBERkUIpCMlNSUrN4rl5W/n96HkAYtrWYdQDt+DjqaEwEREp+9zMLqCowsPDsVgs+b7efffdQpfJyspiyJAhVK1alYoVK9K7d29Onz7toIrLv5/2nqH7lLX8fvQ8Fb09mNovmncebq4QJCIiTsOpjgiNGzeOwYMH57329y/8KqQXX3yRZcuWsWjRIgIDAxk6dCi9evXi119/Le1SyzWrzc7EuD3MWnsYgKY1A5gW05K61SqYXJmIiEjxOFUQ8vf3JyQkpEjzpqam8umnnxIbG8u9994LwOzZs2nSpAkbN27ktttuK81Sy63z2fD4p5vYeiIVgAHtwhhxXxMdBRIREafkVEHo3Xff5a233qJOnTrExMTw4osv4uFR8C5s2bIFq9VKp06d8qZFRERQp04dNmzYcM0glJ2dTXZ2dt7rtLQ0AKxWK1artQT3xvl8v+sUE7a7k2lLxd/Hg3d6NqVb0+qAHavVbnZ55cqVz5qrf+ZKm/rsGOqzY6jP+RW1D04ThJ577jlatmxJlSpVWL9+PSNGjODUqVN88MEHBc6flJSEl5cXlSpVyje9evXqJCUlXXM748ePZ+zYsVdN/+GHH/Dz87upfXBWuXb49rgba065ARbqVDAY2CgL+7EtLD9mdnXlW1xcnNkluAT12THUZ8dQny/LzMws0nymBqHXX3+d9957r9B59uzZQ0REBMOHD8+bFhkZiZeXF8888wzjx4/H29u7xGoaMWJEvm2lpaURGhpKly5dCAhwvYeEnriQyQsLd7Dj1OUjY+1r2Jn8VAcq+JRcz+VqVquVuLg4OnfujKenp9nllFvqs2Ooz46hPud3ZUTnekwNQi+99BIDBw4sdJ569eoVOL1t27bk5uZy9OhRGjdufNX7ISEh5OTkkJKSku+o0OnTpws9z8jb27vAYOXp6elyH6yVu07xypc7SM/KJdDXk/cebkr2kc1U8PF2uV6YxRU/d2ZQnx1DfXYM9fmyovbA1CAUFBREUFDQDS27bds23NzcCA4OLvD9Vq1a4enpyerVq+nduzcA+/bt4/jx47Rr1+6Ga3YFWVYb45fv4V8bLo97taxTiQ9jWhJcwYPlR0wuTkREpAQ5xTlCGzZs4LfffqNDhw74+/uzYcMGXnzxRZ544gkqV64MQEJCAh07duSzzz6jTZs2BAYG8vTTTzN8+HCqVKlCQEAAw4YNo127drpirBBHz2YwJDae3YmXDyk+c3c9Xu7aGE93N52AJyIi5Y5TBCFvb2/mz5/PmDFjyM7Opm7durz44ov5zuWxWq3s27cv38lRkyZNws3Njd69e5OdnU3Xrl2ZMWOGGbvgFL7dnsiIr3dyMTuXyn6efPBoFB0iCj7iJiIiUh44RRBq2bIlGzduLHSe8PBwDMPIN83Hx4fp06czffr00izP6WVZbYz99g/m/X4cgDbhVZjSL4oagb4mVyYiIlK6nCIISek5lHyRIXPj2ZuUjsUCf21fnxc7NcLD3WmeviIiInLDFIRc2DdbT/J/3+wiM8dGtYpeTOobxV0Nb+zkdREREWekIOSCLuXYGL10Fws3nwSgXb2qTHksiuAAH5MrExERcSwFIRez/3Q6Q+bGc+DMRSwWeO7ehjzXsSHubhazSxMREXE4BSEXYRgGi7acZNSSXWRZ7QT5ezOlbxS3N6hmdmkiIiKmURByARnZuby5eBdfb00A4K6G1fjg0SiC/PWYDBERcW0KQuXcnlNpDImN53ByBm4WGN65EX9t3wA3DYWJiIgoCJVXhmEw7/cTjP12N9m5dqoHeDP1sWja1qtqdmkiIiJlhoJQOZSeZeWNb3bx7fZEANo3DuL9Pi2oWlFDYSIiIv9NQaic2ZWQytDYeI6ey8TdzcIrXRvz57vqaShMRESkAApC5YRhGHy+8Rhvf7eHHJudmoE+fBgTTauwKmaXJiIiUmYpCJUDqZesjPh6B8t3JgHQqUl1JvaJpJKfl8mViYiIlG0KQk5ux8kUhsTGc+L8JTzdLbzevQlP3RGOxaKhMBERketREHJShmHwz1+P8u6KPVhtBrUr+zI9piUtQiuZXZqIiIjTUBByQimZObzy5Q7i/jgNQPdmIbzbO5JAX0+TKxMREXEuCkJOJv74BYbFbiUh5RJe7m6MfKAJT94WpqEwERGRG6Ag5CTsdoNP1h3m7yv3kWs3CKvqx/SYljSrFWh2aSIiIk5LQcgJnM/I4eVF2/lx7xkAHoiswfhezfH30VCYiIjIzVAQKuM2HT3PsNitJKVl4eXhxpgHm9KvTaiGwkREREqAglAZZbcbfPTzIT6I24/NblAvqALTY1rSpEaA2aWJiIiUGwpCZdDZi9m8uGAbvxw4C8DD0bV4u2czKnjr2yUiIlKS9Ju1jFl/6CzPz99Gcno2Pp5ujHuoGX1a1dZQmIiISClQECojbHaDD388wNTVB7Ab0DC4ItMfb0mj6v5mlyYiIlJuKQiVAWfSs3hh/jbWHzoHQJ9WtRn7UFP8vPTtERERKU36TWuydQfO8sKCrZy9mIOflztv92xGr5a1zS5LRETEJSgImSTXZmfyqgNMX3MQw4CIEH+mxbSkQXBFs0sTERFxGQpCJrDa7DzxyW/8duQ8ADFt6zDqgVvw8XQ3uTIRERHXoiBkAk93NyJrB7I7MY13ejWnR4uaZpckIiLikhSETPJK1wievC2cOlX9zC5FRETEZbmZXYCr8vJwUwgSERExmYKQiIiIuCynCEJr1qzBYrEU+LVp06ZrLte+ffur5n/22WcdWLmIiIiUZU5xjtDtt9/OqVOn8k178803Wb16Na1bty502cGDBzNu3Li8135+Go4SERGRy5wiCHl5eRESEpL32mq1smTJEoYNG3bdZ3D5+fnlW1ZERETkCqcIQv9r6dKlnDt3jkGDBl133rlz5/LFF18QEhLCgw8+yJtvvlnoUaHs7Gyys7PzXqelpQGXw5fVar354p3Ylf139T44gnrtGOqzY6jPjqE+51fUPlgMwzBKuZYSd9999wGwfPnyQuf7+OOPCQsLo2bNmuzYsYPXXnuNNm3a8PXXX19zmTFjxjB27NirpsfGxmpYTURExElkZmYSExNDamoqAQEB15zP1CD0+uuv89577xU6z549e4iIiMh7ffLkScLCwli4cCG9e/cu1vZ+/PFHOnbsyMGDB6lfv36B8xR0RCg0NJSzZ88W2khXYLVaiYuLo3Pnznh6eppdTrmmXjuG+uwY6rNjqM/5paWlUa1atesGIVOHxl566SUGDhxY6Dz16tXL93r27NlUrVqVHj16FHt7bdu2BSg0CHl7e+Pt7X3VdE9PT32w/k29cBz12jHUZ8dQnx1Dfb6sqD0wNQgFBQURFBRU5PkNw2D27Nn079//hr7J27ZtA6BGjRrFXlZERETKH6e4j9AVP/74I0eOHOFPf/rTVe8lJCQQERHB77//DsChQ4d466232LJlC0ePHmXp0qX079+fu+++m8jISEeXLiIiImWQU1019umnn3L77bfnO2foCqvVyr59+8jMzAQuX3K/atUqJk+eTEZGBqGhofTu3ZuRI0c6umwREREpo5wqCMXGxl7zvfDwcP77vO/Q0FB+/vlnR5QlIiIiTsqphsZERERESpJTHREyw5WjTFdurOjKrFYrmZmZpKWl6YqEUqZeO4b67Bjqs2Ooz/ld+b19vbsEKQhdR3p6OnB5qE1EREScS3p6OoGBgdd83ynvLO1IdrudxMRE/P39r/tcs/Luys0lT5w44fI3lyxt6rVjqM+OoT47hvqcn2EYpKenU7NmTdzcrn0mkI4IXYebmxu1a9c2u4wyJSAgQP/JHES9dgz12THUZ8dQn/+jsCNBV+hkaREREXFZCkIiIiLishSEpMi8vb0ZPXp0gc9ik5KlXjuG+uwY6rNjqM83RidLi4iIiMvSESERERFxWQpCIiIi4rIUhERERMRlKQiJiIiIy1IQkpuWnZ1NVFQUFouFbdu2mV1OuXL06FGefvpp6tati6+vL/Xr12f06NHk5OSYXZrTmz59OuHh4fj4+NC2bVt+//13s0sqd8aPH8+tt96Kv78/wcHB9OzZk3379pldVrn27rvvYrFYeOGFF8wuxWkoCMlNe/XVV6lZs6bZZZRLe/fuxW63M2vWLHbv3s2kSZOYOXMmb7zxhtmlObUFCxYwfPhwRo8eTXx8PC1atKBr166cOXPG7NLKlZ9//pkhQ4awceNG4uLisFqtdOnShYyMDLNLK5c2bdrErFmziIyMNLsUp6LL5+WmrFixguHDh/PVV1/RtGlTtm7dSlRUlNlllWsTJkzgo48+4vDhw2aX4rTatm3LrbfeyrRp04DLzxQMDQ1l2LBhvP766yZXV34lJycTHBzMzz//zN133212OeXKxYsXadmyJTNmzODtt98mKiqKyZMnm12WU9ARIblhp0+fZvDgwXz++ef4+fmZXY7LSE1NpUqVKmaX4bRycnLYsmULnTp1ypvm5uZGp06d2LBhg4mVlX+pqakA+vyWgiFDhnD//ffn+1xL0eihq3JDDMNg4MCBPPvss7Ru3ZqjR4+aXZJLOHjwIB9++CETJ040uxSndfbsWWw2G9WrV883vXr16uzdu9ekqso/u93OCy+8wB133EGzZs3MLqdcmT9/PvHx8WzatMnsUpySjghJPq+//joWi6XQr7179/Lhhx+Snp7OiBEjzC7ZKRW1z/8tISGBbt260adPHwYPHmxS5SI3ZsiQIezatYv58+ebXUq5cuLECZ5//nnmzp2Lj4+P2eU4JZ0jJPkkJydz7ty5QuepV68ejz76KN9++y0WiyVvus1mw93dnccff5x//etfpV2qUytqn728vABITEykffv23HbbbcyZMwc3N/0Nc6NycnLw8/Pjyy+/pGfPnnnTBwwYQEpKCkuWLDGvuHJq6NChLFmyhLVr11K3bl2zyylXFi9ezMMPP4y7u3veNJvNhsViwc3Njezs7HzvydUUhOSGHD9+nLS0tLzXiYmJdO3alS+//JK2bdtSu3ZtE6srXxISEujQoQOtWrXiiy++0A+1EtC2bVvatGnDhx9+CFwetqlTpw5Dhw7VydIlyDAMhg0bxjfffMOaNWto2LCh2SWVO+np6Rw7dizftEGDBhEREcFrr72mYcgi0DlCckPq1KmT73XFihUBqF+/vkJQCUpISKB9+/aEhYUxceJEkpOT894LCQkxsTLnNnz4cAYMGEDr1q1p06YNkydPJiMjg0GDBpldWrkyZMgQYmNjWbJkCf7+/iQlJQEQGBiIr6+vydWVD/7+/leFnQoVKlC1alWFoCJSEBIpw+Li4jh48CAHDx68KmDqYO6N69u3L8nJyYwaNYqkpCSioqJYuXLlVSdQy8356KOPAGjfvn2+6bNnz2bgwIGOL0ikABoaExEREZelMy5FRETEZSkIiYiIiMtSEBIRERGXpSAkIiIiLktBSERERFyWgpCIiIi4LAUhERERcVkKQiIiRdC+fXteeOEFs8sQkRKmGyqKiBTB+fPn8fT0xN/f3+xSRKQEKQiJiIiIy9LQmIg4leTkZEJCQnjnnXfypq1fvx4vLy9Wr15d4DKbNm2ic+fOVKtWjcDAQO655x7i4+Pz3l+zZg1eXl788ssvedP+/ve/ExwczOnTp4Grh8ZmzJhBw4YN8fHxoXr16jzyyCMlvKci4ggKQiLiVIKCgvjnP//JmDFj2Lx5M+np6Tz55JMMHTqUjh07FrhMeno6AwYMYN26dWzcuJGGDRty3333kZ6eDvwn5Dz55JOkpqaydetW3nzzTT755JMCH8S6efNmnnvuOcaNG8e+fftYuXIld999d6nut4iUDg2NiYhTGjJkCKtWraJ169bs3LmTTZs24e3tXaRl7XY7lSpVIjY2lgceeACAnJwc2rZtS6NGjdi1axd33HEHH3/8cd4y7du3JyoqismTJ/P1118zaNAgTp48qXOGRJycjgiJiFOaOHEiubm5LFq0iLlz5+Lt7c3x48epWLFi3teV4bPTp08zePBgGjZsSGBgIAEBAVy8eJHjx4/nrc/Ly4u5c+fy1VdfkZWVxaRJk6657c6dOxMWFka9evV48sknmTt3LpmZmaW+zyJS8jzMLkBE5EYcOnSIxMRE7HY7R48epXnz5tSsWZNt27blzVOlShUABgwYwLlz55gyZQphYWF4e3vTrl07cnJy8q1z/fr1wOUrxM6fP0+FChUK3La/vz/x8fGsWbOGH374gVGjRjFmzBg2bdpEpUqVSmV/RaR0aGhMRJxOTk4Obdq0ISoqisaNGzN58mR27txJcHBwgfP7+/szY8YMnnzySQBOnDhBnTp1mDRpUt4J0IcOHSIqKoqpU6eyYMECcnJyWLVqFW5ulw+c//fQ2P/KyMigUqVKLFiwgF69epXKPotI6dARIRFxOv/3f/9HamoqU6dOpWLFiixfvpynnnqK7777rsD5GzZsyOeff07r1q1JS0vjlVdewdfXN+99m83GE088QdeuXRk0aBDdunWjefPmvP/++7zyyitXre+7777j8OHD3H333VSuXJnly5djt9tp3Lhxqe2ziJQOnSMkIk5lzZo1TJ48mc8//5yAgADc3Nz4/PPP+eWXX/joo48KXObTTz/lwoULtGzZkieffJLnnnsu39Gjv/3tbxw7doxZs2YBUKNGDT7++GNGjhzJ9u3br1pfpUqV+Prrr7n33ntp0qQJM2fOZN68eTRt2rR0dlpESo2GxkRERMRl6YiQiIiIuCwFIREREXFZCkIiIiLishSERERExGUpCImIiIjLUhASERERl6UgJCIiIi5LQUhERERcloKQiIiIuCwFIREREXFZCkIiIiLishSERERExGX9P56ip2/8YRXnAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# 设置斜率 (m) 和 y轴截距 (b)\n",
    "m = 2\n",
    "b = 3\n",
    "\n",
    "# 生成x值\n",
    "x = np.linspace(-5, 5, 100)\n",
    "# 计算对应的y值\n",
    "y = m * x + b\n",
    "\n",
    "# 构建方程字符串，用于图例和标题\n",
    "equation_str = f\"y = {m}x\"\n",
    "if b > 0:\n",
    "    equation_str += f\" + {b}\"\n",
    "elif b < 0:\n",
    "    equation_str += f\" - {abs(b)}\"\n",
    "\n",
    "# 绘制直线\n",
    "plt.plot(x, y, label=equation_str)\n",
    "\n",
    "# 添加标题和轴标签\n",
    "plt.title(f\"Plot of {equation_str}\")\n",
    "plt.xlabel(\"x-axis\")\n",
    "plt.ylabel(\"y-axis\")\n",
    "\n",
    "# 显示网格和图例\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "\n",
    "# 显示图表\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f7b43d82",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.18"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
